Powerful Image/Video Denoising
Digital Imaging Noise
The presence of visual noise in digital imagery is not only an esthetic problem for consumers, but it is also
a serious impediment for computer vision applications where a clean signal is imperative.
Digital images and videos are produced by a camera equipped with an image sensor and an image
processor. Photons traveling through an optical lens hit the sensor, which records the signal but also
generates some level of noise. This sensor noise is then amplified and transformed by subsequent image
processing to produce varieties of processed noise, which are very different in character from sensor noise.
An effective denoiser must be able to suppress both sensor noise and processed noise.
Different noise types (L to R): sensor noise, chromatic upscaling, compression
Effective denoising is hard, as the denoiser must reconstruct the information that has been obscured by
noise. It must determine the correct color of the pixels without introducing blur or otherwise degrading
the image content. This is not a trivial problem. To solve it well, three things need to happen:
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The noise must be analyzed and modelled mathematically;
The image content must be understood spatially (within a single frame) and temporally (between
adjacent frames in case of video) – the more the better;
Information from 1 and 2 is used to replace noisy pixels in in each frame by pixels of the correct
color value.
Furthermore, these three things must happen correctly, consistently, robustly, and quickly. While many
other solutions to this problem have been proposed, most suffer from one or more crucial flaws that
render them impractical for use in real-world situations:
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Image degradation (e.g. blurring, color shift);
Excessive processing time and power consumption;
Parameters need to be tuned by a human to match the image/video content.
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Powerful Image/Video Denoising
The Wrnch Image/Video Denoiser
The Wrnch Image/Video Denoiser produces high quality content with real-time speed from any type of
noisy image source. Wrnch is:
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Automated: Wrnch is fully automated while other methods need manual intervention, such as
defining tuning parameters and gathering noise profiles.
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Comprehensive: Noise models in many systems are oversimplified. Wrnch uses a
comprehensive noise model that can detect the noise power, type and non-uniformity.
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Highest quality: Wrnch suppresses noise while keeping image details (no blurring) and pixel
energy (no color shift).
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Robust:
• Special cases: Unlike other denoising methods that are tuned for specific data and noise,
wrnch does not sacrifice quality in special cases.
• HDR: Wrnch handles two challenging problems of HDR images and videos: highprecision and extreme non-uniformity of noise.
• Subjective blur-noise optimal point: Using a wide variation of data sets and extensive
subjective and objective experiments, wrnch automatically finds the optimal blur-noise
point.
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Fast: Wrnch is highly parallelized, and takes maximal advantage of parallel processing both on
the GPU and the CPU.
Different noise types: denoised by wrnch
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Powerful Image/Video Denoising
The Wrnch SDK
The Wrnch Image/Video Denoiser can be seamlessly integrated into a variety of applications on any
computing platform through the wrnch Denoiser Software Development Kit (SDK). The wrnch Denoiser
SDK is:
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Multi-platform:
• Supports Windows, OSX, Linux, Android;
• Supports various compute devices: CPU, GPU
• Desktop-, mobile-, and cloud-ready.
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Modular: The SDK uses many high fidelity components that can be replaced by faster
components, providing a reasonable variation of speed vs. quality that can be tuned to specific
hardware resources.
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Easily integrated: Delivered as a C++ library with a simple and intuitive API. Speed is boosted
with OpenCL under the hood. Easy and seamless integration for software developers with no
image processing or GPU knowledge.
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Stable and Consistent: Tested nightly on a huge database of images and videos, with samples
from a large array of varied sources.
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Engineered for excellence: The wrnch team of seasoned engineers and scientists have years of
visual computing SDK experience.
Hollywood Quality: Red Giant Denoiser III powered by wrnch.
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